When Brooks Hamilton and Brian Hopkins started AI News and Gurus, it was to bring AI closer to the distribution audience and talk about issues not necessarily related to technology, but to how to think about AI in business. (Register for the May 1 episode.)
This article provides the key insights from their first discussion and outlines how forward-thinking distributors can position themselves for success in an AI-driven future.
Distribution executives over the past couple of years have realized that the realm of intelligence is rapidly evolving from a tool that helps a business to a capability that only the successful distributors will take advantage of. During a recent discussion featuring Hopkins, Hamilton, and John Carrico from Epicor, the message was unmistakable. Companies that fail to embrace AI as a strategic imperative now risk falling behind permanently as the distribution industry undergoes its most profound transformation in decades.
“This isn’t about a feature or a product, or some little add-on that you’re gonna put into your system somewhere,” emphasized Hopkins. “This is really about how you change your whole organization to be AI-first, AI-driven so that you are setting itself up for the next 40, 50 years, and not being one of the laggards in the industry.”
The conversation revealed that distribution leaders must move beyond viewing AI as merely another technological tool and instead recognize it as a fundamental shift in how businesses operate, compete, and deliver value.
The Mindset Shift: Intelligence as a Purchasable Asset
The most profound insight from the panel was conceptualizing AI as an intelligence asset that companies can purchase—like how they might hire talent or invest in training.
“Before we had one option if we wanted more intelligence: more people or more training,” noted Hamilton. “Now we have a third option which is fundamentally different—I can choose to go buy more intelligence for a department in my organization.”
This perspective challenges conventional business thinking. Instead of automatically adding headcount when workloads increase, leaders should consider whether AI capabilities could deliver better outcomes at lower costs.
A Procter & Gamble study cited during the discussion found that teams using AI were 9.2 percentage points more productive than their counterparts and 17% faster. Even more striking, the output of one person using AI tools equaled that of two people working without them.
This productivity boost represents a profound shift in how companies should evaluate their resource allocation. Rather than measuring success by headcount or hours worked, companies need to focus on outcomes and the quality of decisions being made with AI support.
From Periodic to Continuous Optimization
AI offers several powerful pathways to transform distribution operations across multiple business functions. Whether applied to sales and price optimization or back-office productivity for warehouse efficiency, AI is fundamentally changing how distributors operate.
In sales and pricing, AI enables dynamic, real-time adjustments based on market conditions, inventory levels, and customer behavior. For warehouse operations, AI can optimize everything from slotting to picking routes to labor scheduling, creating continuous improvement where once there were only periodic adjustments.
Hopkins shared a telling example from his distribution experience: “When I started with Grainger, I had a branch manager who was good at moving inventory that was fast-moving toward the counter and toward the shipping bench…. Very disciplined. Exceptionally good at it. Problem was that it was data-driven, it was once a month, and it was a huge project—two to three hours every time we did it.”
Today’s AI systems can perform this type of dynamic slotting incrementally every day, ensuring inventory is constantly optimized rather than being adjusted through periodic, labor-intensive projects. Similar improvements are happening with route optimization, where AI can make real-time adjustments based on traffic conditions, and with truck loading, where systems can maximize capacity utilization.
This shift from periodic to continuous optimization represents a significant opportunity for distributors to improve efficiency and customer service while reducing the burden on employees—provided they’re willing to rethink established processes.
Where to Focus AI Investments for Maximum Impact
For distributors wondering where to begin their AI journey, the panel offered clear guidance on which areas typically deliver the greatest returns:
- Sales conversion rate improvements offer the highest potential impact.
- Pricing optimization ranks second in terms of ROI potential.
- Inventory management rounds out the top three priorities.
“If I had half a million dollars as an owner that I want to invest somewhere in my organization,” Hamilton said, “I would look pretty directly at the sales rep journey and the customer journey to see how I can go about improving those via AI.”
While front-end applications may seem less disruptive to implement, the panel cautioned against overlooking back-end operations. Warehouse management, logistics optimization, and reverse logistics represent significant opportunities for efficiency gains, even if they require more substantial process changes.
The key is identifying your biggest pain points where improvements would have the most significant impact on your business—rather than implementing AI for its own sake.
The Emergence of Cognitive ERP Systems
Carrico from Epicor introduced the concept of “cognitive ERP” systems that represent a dramatic evolution from traditional enterprise software. Unlike conventional ERPs that simply process transactions, cognitive systems actively think with users by:
- Understanding patterns across different business functions
- Recommending actions (and sometimes taking them autonomously)
- Interacting conversationally with users
- Learning and improving over time
“Cognitive ERP shifts our role from a provider to a partner, from a system builder to an intelligent enabler,” Carrico explained. “It’s about the awareness, the reasoning, the learning, and the action so that the ERP can understand patterns across different functions, whether it’s sales, operations, finance, inventory.”
This evolution means ERP vendors are increasingly focusing on delivering business outcomes rather than features. “Buyers are less interested in what the software does and more interested in what it can deliver,” noted Carrico. Companies are looking for solutions that improve working capital by a specific percentage, grow margins with AI-driven pricing, or reduce order-to-cash cycles—concrete business results rather than technical capabilities.
Getting Started with AI: Practical Implementation Advice
The panel offered several practical recommendations for distributors beginning their AI journey:
Start with clear business problems. Focus on specific challenges like increasing fill rates, addressing margin erosion, or improving sales team efficiency rather than implementing AI for its own sake.
- Quantify the opportunity. Calculate what a 1% improvement in key metrics would mean financially to help prioritize investments.
- Embed AI into existing workflows. The most successful implementations integrate AI directly into processes rather than treating it as a separate tool.
- Engage users early. Train teams and involve them in implementation to build buy-in and ensure the system meets their needs.
- Iterate quickly. Don’t expect perfection immediately; be prepared to tune models and workflows based on feedback.
Join us at our next show on May 1 as we bring Tracie Deuell from Bostwick-Braun to talk about the AI journey from a distributor’s perspective.
